81 buildings

Downloading Microsoft and Google Building Footprints

This notebook demonstrates how to download Microsoft and Google Building Footprints and merge them into a single vector file.

• Microsoft Global Building Footprints: https://github.com/microsoft/GlobalMLBuildingFootprints
• Google Open Buildings: https://sites.research.google/open-buildings

Uncomment the following line to install leafmap if needed.

In [1]:

# %pip install -U leafmap geopandas

# %pip install -U leafmap geopandas

In [2]:

import leafmap

import leafmap

Specify the country name.

In [3]:

country = "Libya"

country = "Libya"

Specify the number of files to download. Set to None to download all files.

In [4]:

head = 2

head = 2

Download the Microsoft building footprints.

In [5]:

leafmap.download_ms_buildings(
    country, 
    out_dir="buildings", 
    merge_output=f"{country}_ms.shp", 
    head=head
    )

leafmap.download_ms_buildings( country, out_dir="buildings", merge_output=f"{country}_ms.shp", head=head )

Found 84 links for Libya
Downloading 1 of 2: 122003333.geojson
Downloading 2 of 2: 122012202.geojson
Reading 1 of 2: buildings/122003333.geojson
Reading 2 of 2: buildings/122012202.geojson
Merging GeoDataFrames ...
Saving merged file to Libya_ms.shp ...
Saved merged file to Libya_ms.shp

Out[5]:

['buildings/122003333.geojson', 'buildings/122012202.geojson']

Display the Microsoft building footprints.

In [6]:

m = leafmap.Map()
m.add_basemap("SATELLITE")
m.add_vector(f"{country}_ms.shp", layer_name="MS Buildings")
m

m = leafmap.Map() m.add_basemap("SATELLITE") m.add_vector(f"{country}_ms.shp", layer_name="MS Buildings") m

Out[6]:

Download the Google building footprints.

In [7]:

leafmap.download_google_buildings(
    country, 
    out_dir="buildings", 
    merge_output=f"{country}_google.shp", 
    head=head, 
    overwrite=True
    )

leafmap.download_google_buildings( country, out_dir="buildings", merge_output=f"{country}_google.shp", head=head, overwrite=True )

Found 7 links for Libya.

Downloading...
From: https://storage.googleapis.com/open-buildings-data/v3/polygons_s2_level_4_gzip/13d_buildings.csv.gz
To: /home/runner/work/leafmap/leafmap/docs/notebooks/buildings/13d_buildings.csv.gz
100%|██████████| 306k/306k [00:00<00:00, 960kB/s]
Downloading...
From: https://storage.googleapis.com/open-buildings-data/v3/polygons_s2_level_4_gzip/141_buildings.csv.gz
To: /home/runner/work/leafmap/leafmap/docs/notebooks/buildings/141_buildings.csv.gz
100%|██████████| 1.01M/1.01M [00:00<00:00, 2.16MB/s]

Merging GeoDataFrames ...

Display the Google building footprints.

In [8]:

url = 'https://sites.research.google/open-buildings/tiles.geojson'

url = 'https://sites.research.google/open-buildings/tiles.geojson'

In [9]:

m = leafmap.Map()
m.add_basemap("SATELLITE")
m.add_geojson(url, layer_name="Google Building Coverage")
m.add_vector(f"{country}_google.shp", layer_name="Google Buildings")
m

m = leafmap.Map() m.add_basemap("SATELLITE") m.add_geojson(url, layer_name="Google Building Coverage") m.add_vector(f"{country}_google.shp", layer_name="Google Buildings") m

Out[9]:

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Last update: 2023-11-27
Created: 2023-11-27